{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0893a344",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import torch\n",
    "from kan import *\n",
    "import copy\n",
    "\n",
    "\n",
    "seed = 2024\n",
    "torch.manual_seed(seed)\n",
    "np.random.seed(seed)\n",
    "\n",
    "dtype = torch.get_default_dtype()\n",
    "\n",
    "# Download data: https://colab.research.google.com/github/deepmind/mathematics_conjectures/blob/main/knot_theory.ipynb#scrollTo=l10N2ZbHu6Ob\n",
    "df = pd.read_csv(\"./knot_data.csv\")\n",
    "df.keys()\n",
    "\n",
    "X = df[df.keys()[1:]].to_numpy()\n",
    "mean = np.mean(X, axis=0)\n",
    "std = np.std(X, axis=0)\n",
    "X = (X - mean[np.newaxis,:])/std[np.newaxis,:]\n",
    "\n",
    "# normalize X\n",
    "X_mean = np.mean(X, axis=0)\n",
    "X_std = np.std(X, axis=0)\n",
    "X = (X - X_mean[np.newaxis,:])/X_std[np.newaxis,:]\n",
    "input_normalier = [X_mean, X_std]\n",
    "\n",
    "dataset = {}\n",
    "num = X.shape[0]\n",
    "n_feature = X.shape[1]\n",
    "train_ratio = 0.8\n",
    "train_id_ = np.random.choice(num, int(num*train_ratio), replace=False)\n",
    "test_id_ = np.array(list(set(range(num))-set(train_id_)))\n",
    "dataset['train_input'] = torch.from_numpy(X[train_id_]).type(dtype)\n",
    "dataset['test_input'] = torch.from_numpy(X[test_id_]).type(dtype)\n",
    "\n",
    "def construct_contrastive_dataset(tensor):\n",
    "    y = copy.deepcopy(tensor)\n",
    "    for i in range(y.shape[1]):\n",
    "        y[:,i] = y[:,i][torch.randperm(y.shape[0])]\n",
    "    return y\n",
    "\n",
    "dataset['contrastive_train_input'] = construct_contrastive_dataset(dataset['train_input'])\n",
    "dataset['contrastive_test_input'] = construct_contrastive_dataset(dataset['test_input'])\n",
    "\n",
    "dataset['train_label'] = torch.cat([torch.ones(dataset['train_input'].shape[0],1), torch.zeros(dataset['contrastive_train_input'].shape[0],1)], dim=0)\n",
    "dataset['train_input'] = torch.cat([dataset['train_input'], dataset['contrastive_train_input']], dim=0)\n",
    "\n",
    "dataset['test_label'] = torch.cat([torch.ones(dataset['test_input'].shape[0],1), torch.zeros(dataset['contrastive_test_input'].shape[0],1)], dim=0)\n",
    "dataset['test_input'] = torch.cat([dataset['test_input'], dataset['contrastive_test_input']], dim=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e262aeca",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checkpoint directory created: ./model\n",
      "saving model version 0.0\n",
      "saving model version 0.1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " train_loss: 1.70e-01 | reg: 1.34e+01 | train_acc: 9.68e-01 | test_acc: 9.69e-01 |:  74%|▋| 74/100 ["
     ]
    }
   ],
   "source": [
    "def train_acc():\n",
    "    return torch.mean(((model(dataset['train_input']) > 0.5) == dataset['train_label']).float())\n",
    "\n",
    "def test_acc():\n",
    "    return torch.mean(((model(dataset['test_input']) > 0.5) == dataset['test_label']).float())\n",
    "\n",
    "model = KAN(width=[n_feature,1,1], grid=5, k=3, seed=seed)\n",
    "model.fix_symbolic(1,0,0,'gaussian',fit_params_bool=False)\n",
    "model.fit(dataset, lamb=0.001, batch=1024, metrics=[train_acc, test_acc], display_metrics=['train_loss', 'reg', 'train_acc', 'test_acc']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ede24f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# seed = 2024\n",
    "model.plot(scale=1.0)\n",
    "\n",
    "n = 18\n",
    "for i in range(n):\n",
    "    plt.gcf().get_axes()[0].text(1/(2*n)+i/n-0.005,-0.02,df.keys()[1:][i], rotation=270, rotation_mode=\"anchor\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a3fb6b7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 22 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# seed = 0\n",
    "model.plot(scale=1.0)\n",
    "\n",
    "n = 18\n",
    "for i in range(n):\n",
    "    plt.gcf().get_axes()[0].text(1/(2*n)+i/n-0.005,-0.02,df.keys()[1:][i], rotation=270, rotation_mode=\"anchor\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
